Global Canny algorithm based on Canny edge detector framework in magnetic resonance imaging

Magnetic resonance imaging is an important modality in the diagnosis and pathology detection. Edge detection is used for image segmentation and feature extraction as part of the medical image analysis. There is no ideal and universal algorithm which performs perfectly under all conditions. Conventional Canny edge detector is not suitable to be used in Magnetic resonance images that contaminated by Rician noise. In this paper, we propose the use of customized non-local means into the Canny edge detector instead of Gaussian smoothing in the conventional Canny edge detector to effectively remove Rician noise while preserving edges in Magnetic resonance image of an internal organ. The result shows that our method can yield better edge detection than conventional method, with minimal false edge detection. The proposed method undergoes several attempts of parameter adjustment to detect true edges successfully using optimal parameter setting.